How Much a Curveball Spins Does Not Correlate with Success at the Major League Level

Every kid that grows up with the aspiration of being a pitcher in the sport of baseball starts out learning how to throw a normally gripped fastball. With the exception of a few anomalies, such as knuckleballers, being able to command one’s fastball and execute it profoundly is a major key to any pitcher’s success as they develop and move forward from little league style baseball into the more competitive travel ball and high school level of play. Eventually having a solid fastball is not enough to be successful once hitters become stronger, develop timing skills, and learn the ins and outs of the strike zone. This is where the development of breaking pitches comes into play and the curveball is one of the first pitches that is experimented with by young pitchers.

The grip and throwing motion of a curveball is designed to create top-spin on the ball, which results in downward movement with 12-6 or 11-7 action. The spin, movement, and pitch speed of a curveball is vastly different than a fastball’s, which is why it so effective early on in baseball.

Fast forward to Major League Baseball and the curveball’s unique trajectory and attributes continue to make it a staple in a plethora of Major League pitcher’s arsenals. Star-pitchers like Clayton Kershaw, Max Scherzer, Jake Arrieta, Marcus Stroman, Corey Kluber and so many more make their million dollar livings by being able to freeze opposing hitters with the breaking ball.

The key attribute that makes the curveball unique is the aforementioned top-spin that is created when a pitcher delivers the pitch. A relatively new measure of a curveball’s trajectory and effectiveness is the pitch’s Spin Rate. When a pitcher releases a pitch, it spins thus creating the “life” of a pitch. For example, a fastball that spins at higher speeds will have a rising effect on opposing hitters. Measured in revolutions per minute, a pitch’s Spin Rate has just as, if not more, impact on the result of a pitch than its recorded velocity.

MLB Statcast is a relatively new data driven tool that gives all thirty teams and their fans access to data and analytics that would be nearly impossible to account for with just viewing a game with the naked eye. Spin Rate is one of the statistics tracked by Statcast that scouts and front offices have begun to use to help them evaluate the effectiveness of individual pitches. Scouts can look at opposing batting average and other counting stats to see how well a pitcher executes a single pitch, but all of those methodologies take into account the hitter as well. Spin Rate on the other hand is solely based on the pitcher’s release and skillset, which makes it a very enticing stat to analyze for a pitcher’s raw talent.

For an effective curveball, a higher Spin Rate would presumably result in more downward movement, deception, and overall effectiveness. While this makes logical sense, this is not always the case. The following chart contains two different data sets. The first data set is the Average Spin Rate in revolutions per minute for the top thirty pitchers in wCB, among qualified pitchers, in 2017. The second statistic is wCB, also known as the Linear Weights of a curveball. These pitch values are calculated by FanGraphs to determine how effective a pitcher’s pitch has been over the course of a season. This measure takes into account the run expectancy in each given count where the pitcher throws a particular pitch, which in this case is the curveball. A higher wCB indicates that a pitcher’s curveball has been effective in specific counts and illustrates how successful the pitch has been to the pitcher. While this stat cannot necessarily, along with other pitching stats, tell the whole story behind a particular pitch due to other confounding variables, it gives a foundation for evaluators to use. This stat in particular favors starting pitchers as well due to the fact they throw more curveballs over the course of a season due to their higher pitch and inning counts, so only starting pitchers will be a part of the following data set. The second data set is the Average Spin Rate in revolutions per minute for the top fourteen pitchers in wCB, among qualified pitchers, thus far in 2017.

Name

Spin-rate

wCB

Corey Kluber

2591

37.8

Aaron Nola

2543

18.3

Stephen Strasburg

2792

13.2

Jimmy Nelson

2555

9.1

Clayton Kershaw

2365

7.4

Carlos Carrasco

2653

7.1

Zack Greinke

2591

7.1

Drew Pomeranz

2548

7

Trevor Bauer

2548

6.8

Alex Cobb

2536

6

Ivan Nova

2353

5

Jason Vargas

2491

4.7

Gio Gonzalez

2706

4.7

Robbie Ray

2038

4.6

Tanner Roark

2719

4.3

German Marquez

2673

3.7

Michael Wacha

2234

3.6

Masahiro Tanaka

2446

2.8

Matt Moore

2393

1.7

Jeff Samardzija

2312

1.6

Jake Arrieta

2704

1.5

Max Scherzer

2506

1.3

Carlos Martinez

2134

0.7

Sonny Gray

2890

0.6

Jhoulys Chacin

2483

0.5

Marcus Stroman

2741

0.1

Jacob deGrom

2555

0.1

Dylan Bundy

2241

0

Ricky Nolasco

2546

0

Jose Quintana

2186

-0.2

Corey Kluber, by far, has had the most effective curveball in 2017 in terms of wCB, which makes sense due to the CY Young caliber season he put together, However, he only has the ninth highest Spin Rate among the pitchers documented in the table. 2016’s CY Young winner Rick Porcello has a higher Average Spin Rate than all but one of the pitchers in the table above, however, his wCB is sitting at a below average -3.3. Graphing a lined scatterplot of the data depicts more about the relationship between the two sets of data.

The line of best fit and R-squared value are very telling of the relationship between the two data sets. The line of best fit displays a very weak positive correlation, which could potentially become even weaker if I included more negative wCB values. An R-squared value of .0462 illustrates the fact that only 4.62% of wCB can be explained by Spin Rate. These two observations suggest there is not a concrete relationship between wCB and the Average Spin Rate of a pitcher’s curveball, which means that just because one’s curveball has the most spin, doesn’t translate to overwhelming success with the pitch.

In conclusion, a pitcher can have the most effective curveball in the sport in terms of movement, but that will not directly result in fantastic numbers and individual statistics. If a pitcher cannot setup the pitch with the rest of their arsenal, locate the pitch correctly, and take advantage of a hitter’s weaknesses, then their curveball becomes utterly useless. There is not a specific benchmark of Spin Rate needed to be a successful Major League pitcher as evidenced by the wide range of Spin Rate values and their corresponding wCB values. Rather a successful curveball is dependent on a formula of various factors including location, execution, arm slot, Spin Rate, and more.